• Advances in concrete construction
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• v.11 no.1
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• pp.1-9
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• 2021

This article discusses the issue of optimizing controller design issues, in which the artificial intelligence (AI) evolutionary bat (EB) optimization algorithm is combined with the fuzzy controller in the practical application of the building. The controller of the system design includes different sub-parts such as system initial condition parameters, EB optimal algorithm, fuzzy controller, stability analysis and sensor actuator. The advantage of the design is that for continuous systems with polytypic uncertainties, the integrated H2/H∞ robust output strategy with modified criterion is derived by asymptotically adjusting design parameters. Numerical verification of the time domain and the frequency domain shows that the novel system design provides precise prediction and control of the structural displacement response, which is necessary for the active control structure in the fuzzy model. Due to genetic algorithm (GA), we use a hierarchical conditions of the Hurwitz matrix test technique and the limits of average performance, Hierarchical Fitness Function Structure (HFFS). The dynamic fuzzy controller proposed in this paper is used to find the optimal control force required for active nonlinear control of building structures. This method has achieved successful results in closed system design from the example.

• Earthquakes and Structures
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• v.17 no.3
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• pp.307-315
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• 2019

Building prediction and control theory have been drawing the attention of many scientists over the past few years because design and control efficiency consumes the most financial and energy. In the literature, many methods have been proposed to achieve this goal by trying different control theorems, but all of these methods face some problems in correctly solving the problem. The Evolutionary Bat (EB) Algorithm is one of the recently introduced optimization methods and providing researchers to solve different types of optimization problems. This paper applies EB to the optimization of building control design. The optimized parameter is the input to the fuzzy controller, which gives the status response as an output, which in turn changes the state of the associated actuator. The novel control criterion for guarantee of the stability of the system is also derived for the demonstration in the analysis. This systematic and simplified controller design approach is the contribution for solving complex dynamic engineering system subjected to external disturbances. The experimental results show that the method achieves effective results in the design of closed-loop system. Therefore, by establishing the stability of the closed-loop system, the behavior of the closed-loop building system can be precisely predicted and stabilized.

• Smart Structures and Systems
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• v.26 no.6
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• pp.797-807
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• 2020

Due to the influence of nonlinearity and time-variation, it is difficult to establish an accurate model of concrete frame structures that adopt active controllers. Fuzzy theory is a relatively appropriate method but susceptible to human subjective experience to decrease the performance. This paper proposes a novel artificial intelligence based EBA (Evolved Bat Algorithm) controller with machine learning matched membership functions in the complex nonlinear system. The proposed affine transformed membership functions are adopted and stabilization and performance criterion of the closed-loop fuzzy systems are obtained through a new parametrized linear matrix inequality which is rearranged by machine learning affine matched membership functions. The trajectory of the closed-loop dithered system and that of the closed-loop fuzzy relaxed system can be made as close as desired. This enables us to get a rigorous prediction of stability of the closed-loop dithered system by establishing that of the closed-loop fuzzy relaxed system.

• Ocean Systems Engineering
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• v.12 no.2
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• pp.159-172
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• 2022

To ensure stable performance, adaptive regulators with new theories are designed for steel-covered offshore platforms to withstand anomalous wave loads. This model shows how to control the vibration of the ocean panel as a solution using new results from Lyapunov's stability criteria, an evolutionary bat algorithm that simplifies computational complexity and utilities. Used to reduce the storage space required for the method. The results show that the proposed operator can effectively compensate for random delays. The results show that the proposed controller can effectively compensate for delays and random anomalies. The improved prediction method means that the vibration of the offshore structure can be significantly reduced. While maintaining the required controllability within the ideal narrow range.